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Since July 2022, the Yangtze River basin has experienced the most severe hydro-meteorological drought since record collection started in 1961, which has greatly affected the ecological environment of the Dongting Lake (DTL) basin. To investigate the effects of drought events on the eutrophication and phytoplankton community structure of DTL, the lake was sampled twice in August and September 2022 based on the water level fluctuations resulting in 47 samples. Furthermore, we combined the comprehensive trophic level index (TLI) and phytoplankton Shannon–Wiener diversity index (H) to characterize and evaluate the eutrophication status. The key influencing factors of the phytoplankton community were identified using redundancy analysis (RDA), hierarchical partitioning, and the Jaccard similarity index (J). Our results showed that the TLI of DTL changed from light–moderate eutrophication status (August) to mesotrophic status (September), whereas the H changed from light or no pollution to medium pollution. The phytoplankton abundance in August (122.06 × 104 cells/L) was less than that in September (351.18 × 104 cells/L) in DTL. A trend in phytoplankton community succession from Bacillariophyta to Chlorophyta and Cyanophyta was shown. The combination of physiochemical and ecological assessment more accurately characterized the true eutrophic status of the aquatic ecosystem. The RDA showed that the key influencing factors in the phytoplankton community were water temperature (WT), pH, nitrogen and phosphorus nutrients, and the permanganate index (CODMn) in August, while dissolved oxygen (DO) and redox potential (ORP) were the key factors in September. Hierarchical partitioning further indicated that temporal and spatial variations had a greater impact on the phytoplankton community. And the J of each region was slightly similar and very dissimilar, from August to September, which indicated a decreased hydrological connectivity of DTL during drought. These analyses indicated that the risk to the water ecology of DTL intensified during the summer–autumn drought in 2022. Safeguarding hydrological connectivity in the DTL region is a prerequisite for promoting energy flow, material cycle, and water ecosystem health. [ABSTRACT FROM AUTHOR]

Background: The objective of this retrospective, multicenter study was to analyze the factors associated with the development of urogenital sepsis after percutaneous nephrolithotomy (PCNL) and to establish a nomogram prediction model of urogenital sepsis after PCNL., Methods: A total of 2066 postoperative PCNL patients were included from three medical institutions: Zunyi Medical University Hospital, Beijing Jishuitan Hospital Guizhou Hospital, and Fenggang County People's Hospital. Clinical data of 1623 patients from the Department of Urology of Zunyi Medical University Hospital were randomized into a training cohort (Zunyi training cohort, N.=1139) and an internal validation cohort (Zunyi internal validation cohort, N.=484) using computer generated random numbers in a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed on the compliance training cohort to identify risk factors for urogenital sepsis after PCNL and to develop a column line graph prediction model based on these risk factors. Finally, Zunyi internal validation cohort and two external validation cohorts (Guiyang external cohort, N.=306; Fenggang external cohort, N.=137) were used to validate the prognostic accuracy of the nomogram prediction model. R4.2.2 statistical software was used for all statistical data analyses., Results: Multifactorial logistic regression analysis of the Zuiyi training cohort (N.=1139) identified five independent risk factors associated with urogenital sepsis after PCNL, including urine culture positivity (odds ratio [OR]=5.29, P<0.001), urine nitrite positivity (OR=5.97, P<0.001), operation time ≥60 min (OR=4.4, P=0.0037), residual stone (OR=5.18, P<0.001), and size ≥30 mm (OR=3.22, P=0.0086). Nomogram were constructed based on these independent risk factors. The area under the curve (AUC) of the nomogram model was 0.907 in the in-progress sample and 0.948 after internal validation. The AUC of the model was 0.855 and 0.804 after external validation of the Guiyang external validation cohort and the Fenggang validation cohort, respectively, indicating good discrimination ability. The calibration curves of the nomogram showed good agreement, and the decision curve analysis demonstrated high clinical utility., Conclusions: Based on the clinical independent risk factors such as positive urine culture, positive urine nitrite, operation time ≥60min, stone residue, stone size ≥30mm, nomogram prediction model of urogenital sepsis after PCNL was established, which can provide reference for urologists to develop preoperative evaluation and treatment strategies for patients with percutaneous nephrolithotomy.